Collaborative optimization of task scheduling and multi-agent path planning in automated warehouses

Abstract Task scheduling (TS) and multi-agent-path-finding (MAPF) are two cruxes of pickup-and-delivery in automated warehouses. In this paper, the optimized simultaneously. Firstly, system model, task path model established, respectively. Then, a algorithm based on enhanced HEFT, heuristic MAPF TS- proposed to solve combinatorial optimization problem. EHEFT, novel rank priority rule is used determine sequencing allocation. algorithm, CBS with rules designed for search. Subsequently, TS-MAPF which combines EHEFT proposed. Finally, algorithms tested separately against relevant typical at different scales. The experimental results indicate that exhibited good performance.